Generalized cross-validation (GCV) is a widely used parameter selection criterion for spline smoothing, but it can give poor results if the sample size n is not sufficiently large. An effective way to overcome this is to use the more stable criterion called robust GCV (RGCV). The main computational
Surface approximation by spline smoothing and generalized cross-validation
β Scribed by Hongmin Lu; Frank H. Mathis
- Publisher
- Elsevier Science
- Year
- 1992
- Tongue
- English
- Weight
- 505 KB
- Volume
- 34
- Category
- Article
- ISSN
- 0378-4754
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β¦ Synopsis
Lu, H. and F.H. Mathis, Surface approximation by spline smoothing and generalized cross-validation, Mathematics and Computers in Simulation 34 (1992) 541-549.
A technique is developed to approximate multi-dimensional surfaces based on smoothing splines. The tensor product is used to extend a one-dimensional spline basis to higher dimensions. The method of generalized cross-validation is applied to choose the smoothing parameter which is computed with the aid of the generalized singular value decomposition of the design and penalty matrices. Numerical examples are also presented to illustrate the technique.
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